Borrowing it
Nothing to install: this file belongs to Aviator-Coding/home-ops. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Aviator-Coding/home-ops/main/.claude/skills/intel-gpu/SKILL.mdgit clone --depth 1 https://github.com/Aviator-Coding/home-opsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aviator-coding/home-ops/intel-gpu)<a href="https://agentmods.dev/skills/aviator-coding/home-ops/intel-gpu"><img src="https://agentmods.dev/badge/skills/aviator-coding/home-ops/intel-gpu.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00093 | $0.00933 |
| Opus 5 | $0.00046 | $0.00466 |
| Sonnet 5 | $0.00019 | $0.00187 |
| Haiku 4.5 | $0.00009 | $0.00093 |
Grade A, and why
intel-gpu scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Intel GPUs: device plugins, VA-API and telemetry
Relocated verbatim from AGENTS.md on 2026-09-01 so it loads only when this subsystem is in play.
The text below is unchanged; only line breaks were inserted. AGENTS.md keeps a one-sentence pointer.
Add new findings here or to the owning document, not back into AGENTS.md - see its
"Maintaining this file" section for the rule.
-
NEVER rename a DRM device node with
generic-device-plugin'smountPath, and never ship a GPU change without running the VA-API check. Theb70group remaps the Arc B70 tocard0/renderD128; that rename is fatal to VA-API, because libdrm ignores the path you pass,fstat()s the fd, reads/sys/dev/char/<major>:<minor>/ueventand reopens the canonicalDEVNAMEit finds there (dri/renderD129) - a path the container does not have.vaGetDisplayDRM()then fails before any driver loads. Level Zero (vllm, comfyui) opens whatever/dev/dri/render*exists and is unaffected, so the AI stack stays green while transcoding is completely dead; that asymmetry hid a total 3-day Tdarr outage (2026-08-26, PR #1443). VA-API consumers must usedevic.es/b70-vaapi, which exposes the same card under its kernel names. Two related traps in the same config: its device IDs aresha1(count + every host path in the group), so adding a path to an existing group changes all its IDs and invalidates kubelet's live allocations for pods holding that resource (add a new group instead); and the config is asubPathmount, which kubelet never refreshes, so theconfigMapGeneratorhash must stay enabled or a config-only edit is inert until someone restarts the DaemonSet by hand. Allocatable capacity is not proof that transcoding works - verification commands:docs/media-stack.md"Verifying VA-API after a GPU change"; mechanism and evidence:docs/ai-gpu-changelog.md(2026-08-29). -
No xpu-smi/level-zero/DCGM-equivalent GPU exporter is deployed, so per-engine busy %, VRAM utilization, and clocks are not queryable in Prometheus for either Intel GPU. Verified live 2026-08-26 while building
ai/gpu-node-dashboard. What does exist: the discrete Arc B70 (talos-3 only,devic.es/b70) surfaces a kernelxe-driver hwmon chip (node_hwmon_chip_names{chip_name="xe"}, chip id0000:02:01_0_0000:03:00_0) withtemp2=package/temp3=VRAM (node_hwmon_temp_celsius),power1cap/crit (node_hwmon_power_cap_watt/_crit_watt, static config values, not live draw),fan1RPM (node_hwmon_fan_rpm), and energy countersenergy1=card/energy2=package (node_hwmon_energy_joule_total,rate()them for live watts - there is no direct power-draw gauge). The fleet iGPU (gpu.intel.com/xe, on-die, all 3 nodes) has no dedicated hwmon chip at all - only kube-state-metrics' device-pluginkube_node_status_allocatable/kube_pod_container_resource_requests{resource="gpu_intel_com_xe"}show allocation/usage, no thermal or utilization signal. Dashboard and verified panel list:kubernetes/apps/base/ai/gpu-node-dashboard/app/gpu-node.json.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 16 lines · 93 tokens per session scan A f648e0ffc325
intel-gpu is a skill published in the GitHub repository Aviator-Coding/home-ops (2 stars, last pushed today), licensed MIT. It adds 93 tokens to every session and 933 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.
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